Online education platform having an instructor dashboard

ABSTRACT

According to an aspect, an online education platform may be configured to provide an online course over a network to a plurality of computing devices. The online course may provide education content in which learners view and interact with the education content. The online education platform may include an online course analyzer to determine performance data associated with learners&#39; engagement with the education content including an engagement metric indicating a level of engagement of the learners with the education content during a session of the online course, and provide the performance data via an instructor dashboard. The online course analyzer may include a content editor configured to edit the education content based on the performance data including changing at least a portion of the education content based on the performance data before a completion of the online course.

BACKGROUND

An online education platform provides a system that delivers onlinecourses to learners through network-connected devices. The onlineeducation platform may provide a mechanism to allow an educator tocreate educational content for a particular online educational course.In some examples, the online education platform provides a coursebuilder in which the educator uses to create the educational content forthe online educational course. However, in some examples, when creatingan on-line course, creativity is often limited because the platform doesnot provide flexibility in adjusting and modifying the educationcontent. Furthermore, the technical knowledge to implement certainchanges is often beyond the technical expertise of the educators. Assuch, some conventional online education platforms are relatively rigid,uniform, and standard, which can hinder learning.

SUMMARY

According to an aspect, a system may include at least one processor, anda non-transitory computer-readable medium configured to store executableinstructions that when executed by the at least one processor areconfigured to implement an online education platform configured toprovide an online course over a network to a plurality of computingdevices. The online course may provide education content in whichlearners view and interact with the education content. The onlineeducation platform may include an online course analyzer configured toprovide an instructor dashboard on a computing device associated with aninstructor of the online course. The online course analyzer maydetermine performance data associated with learners' engagement with theeducation content including an engagement metric indicating a level ofengagement of the learners with the education content during a sessionof the online course. The online course analyzer may include a contenteditor configured to edit the education content based on the performancedata including changing at least a portion of the education contentbased on the performance data before a completion of the online course.

The system may include one or more of the following features (or anycombination thereof). In some examples, the content editor may interfacewith an authoring tool executing on the computing device associated withthe instructor, where the authoring tool is integrated within theinstructor dashboard such that the instructor can initiate an edit ofthe education content while viewing the performance data. The onlinecourse analyzer may include a learner tracking unit configured to tracklearners' interactions with the education content during the session ofthe online course, and the online course analyzer may be configured todetermine the engagement metric based on the learners' interactions. Theonline course analyzer may include a grading unit configured toautomatically grade assessments taken by the learners, and provide oneor more grading metrics via the instructor dashboard based on the gradedassessments. The online education platform may be configured to providea first version of an assessment of the online course, and the contenteditor may be configured to change at least a portion of the firstversion of the assessment to create a second version of the assessment.The online course analyzer may include an assessment comparatorconfigured to compare the first version of the assessment with thesecond version of the assessment, where the online course analyzer maybe configured to provide results of the comparison via the instructordashboard. The online course analyzer may include a content evaluatorconfigured to evaluate a quality of the education content based on theperformance data, where the online course analyzer includes an alertingunit configured to generate an alert based on a quality of at least aportion of the educational content being equal to or below a thresholdvalue. The online education platform may be configured to provide theeducation content with a first feature, and the online educationplatform is configured to provide the education content with a secondfeature, where the online course analyzer may include a featurecomparator configured to compare performance data having the firstfeature with performance data having the second feature determine whichof the first feature or the second feature is better than the other. Theonline course analyzer may be configured to provide a histogramreflecting a grade distribution of an assessment of the online course.The online course analyzer may include a survey unit configured toprovide a first survey to learners of an online class associated with afirst school, and provide a second survey to learners of the onlineclass associated with a second school, where the first survey isequivalent to the second survey, and the survey unit may be configuredto compare results of the first survey to results of the second survey.

According to an aspect, a non-transitory computer-readable medium storesexecutable instructions that when executed by at least one processor areconfigured to implement an online education platform. The onlineeducation platform may be configured to provide an online course over anetwork to a plurality of computing devices. The online course mayprovide education content in which learners view and interact with theeducation content. The online education platform may be configured todetermine performance data associated with learners' engagement with theeducation content including an engagement metric indicating a level ofengagement of the learners with the education content during a sessionof the online course, and a grading metric associated with an assessmentof the education content, provide an instructor dashboard on a computingdevice associated with an instructor of the online course, where theinstructor dashboard provides the engagement metric and the gradingmetric, and the instructor dashboard provides a link to initiate an editof the assessment in relation to at least one of the engagement metricand the grading metric, and provide an authoring tool upon activation ofthe link, where the authoring tool defines a text editor configured toreceive a modification to education content that defines the assessment.

The non-transitory computer-readable medium may include one or more ofthe following features (or any combination thereof). The onlineeducation platform may be configured to track learners' interactionswith the education content during the session of the online course anddetermine the engagement metric based on the learners' interactions. Theonline education platform may be configured to automatically grade theassessment taken by each of the learners who completed the assessmentand provide the grading metric via the instructor dashboard based on thegraded assessment. The online education platform may be configured toprovide a first version of the assessment, change at least a portion ofthe first version of the assessment to create a second version of theassessment, compare the first version of the assessment with the secondversion of the assessment, and provide results of the comparison via theinstructor dashboard. The online education platform may be configured toevaluate a quality of the education content based on the performancedata, and generate an alert based on a quality of at least a portion ofthe educational content being equal to or below a threshold value. Theonline education platform may be configured to provide the educationcontent with a first feature, provide the education content with asecond feature, and compare performance data having the first featurewith performance data having the second feature determine which of thefirst feature or the second feature is better than the other. In someexamples, the online education platform may be configured to provide ahistogram reflecting a grade distribution of the assessment.

According to an aspect, a method for implementing an online educationplatform that provides an online course over a network to a plurality ofcomputing devices in which learners view and interact with educationcontent of the online course may include determining, by at least oneprocessor, performance data associated with learners' engagement withthe education content including an engagement metric indicating a levelof engagement of the learners with the education content during asession of the online course and a grading metric associated with anassessment of the education content, providing, by the at least oneprocessor, an instructor dashboard on a computing device associated withan instructor of the online course, where the instructor dashboardprovides the engagement metric and the grading metric, and theinstructor dashboard provides a link to initiate an edit of theassessment in relation to at least one of the engagement metric and thegrading metric, and providing, by the at least one processor, anauthoring tool upon activation of the link, where the authoring tooldefines a text editor configured to receive a modification to educationcontent that defines the assessment.

The method may include one or more of the following features (or anycombination thereof). The method may include tracking, by the at leastone processor, learners' interactions with the education content duringthe session of the online course, and determining, by the at least oneprocessor, the engagement metric based on the learners' interactions.The method may include automatically grading, by the at least oneprocessor, the assessment taken by each of the learners who completedthe assessment, and providing, by the at least one processor, thegrading metric via the instructor dashboard based on the gradedassessment. The method may include providing, by the at least oneprocessor, the education content with a first feature, providing, by theat least one processor, the education content with a second feature, andcomparing, by the at least one processor, performance data having thefirst feature with performance data having the second feature determinewhich of the first feature or the second feature is better than theother.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features will beapparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a system configured to support anonline education platform according to an implementation.

FIG. 2 illustrates education content that is operable across multipleimplementations of a learner application of FIG. 1 according to animplementation.

FIG. 3 illustrates a graphical representation of a perspective of aneducation markup language (EML) format according to an implementation.

FIG. 4 illustrates a screenshot of an authoring tool of an instructorapplication that allows the instructor to edit the education contentaccording to an implementation.

FIG. 5 illustrates another screenshot of the authoring tool of theinstructor application that allows the instructor to edit the educationcontent according to an implementation.

FIG. 6 illustrates an example of hypertext markup language (HTML) as afirst format according to an implementation.

FIG. 7 illustrates the education content provided by the instructor viathe authoring tool, which has been converted to the EML format accordingto an implementation.

FIG. 8 illustrates an example of a screenshot of the education contentrendered by the learner application implemented as a native mobileapplication according to an implementation.

FIG. 9 illustrates an example of a screenshot of the education contentrendered by the learner application implemented as a web applicationaccording to an implementation

FIG. 10 illustrates a screenshot of the authoring tool that allows theinstructor to change the assessment in response to feedback according toan implementation.

FIG. 11 illustrates another screenshot of the authoring tool that allowsthe instructor to change the assessment in response to feedbackaccording to an implementation.

FIG. 12 illustrates another screenshot of the authoring tool that allowsthe instructor to change the assessment in response to feedbackaccording to an implementation.

FIG. 13 illustrates a screenshot of the instructor dashboard accordingto an implementation.

FIG. 14 illustrates another screenshot of the instructor dashboardaccording to an implementation.

FIG. 15 illustrates another screenshot of the instructor dashboardaccording to an implementation.

FIG. 16 illustrates a screenshot of the instructor dashboard depictinganalytic results according to an implementation.

FIG. 17 illustrates another screenshot of the instructor dashboarddepicting analytic results according to an implementation.

FIG. 18 illustrates a screenshot of the instructor dashboard depictinggrading metrics by questions for an assessment according to animplementation.

FIG. 19 illustrates a screenshot of the instructor dashboard depictingperformance data for an assessment of an online course according to animplementation.

FIG. 20 illustrates a screenshot of the instructor dashboard depictingperformance data for a first version assessment of an online courseaccording to an implementation.

FIG. 21 illustrates a screenshot of the instructor dashboard depictingperformance data for a second version assessment of the online courseaccording to an implementation.

FIG. 22 illustrates a screenshot of the instructor dashboard depictingsurvey results according to an implementation.

FIG. 23 illustrates a flowchart depicting example operations of thesystem of FIG. 1 according to an implementation.

FIG. 24 illustrates a flowchart depicting example operations of thesystem of FIG. 1 according to another implementation.

DETAILED DESCRIPTION

FIG. 1 is a schematic diagram of a system 100 configured to support anonline education platform 102 according to an implementation. The system100 includes a computing device 101 configured to host the onlineeducation platform 102. The online education platform 102 may beconfigured to provide, over a network, online courses 104 to learners(students) via their computing devices 174. Referring to FIG. 1, thecomputing device 174 refers to a device used by a learner of an onlinecourse 104, and the learner uses his/her computing device 174 to connectto the online education platform 102 and receive education content 136corresponding to the online course 104 from the online educationplatform 102. For instance, the online course 104 may specify theeducation content 136 that is delivered over the network to a learnerapplication 176 of the computing device 174 in which a learner can viewand interact with the education content 136.

The education content 136 may include a variety of information such as alecture 180, an assessment 182 (e.g., quiz, test, assignment, etc.),education data 184 (e.g., text, audio, images, tables, math expressions,graphs, etc. for learning), and a survey 188. The lecture 180 mayinclude one or more video and/or audio clips that correspond to aparticular online course 104 (or a portion, module, or segment thereof).The online course 104 may specify a number of various lectures 180 thatare viewed by the learners at different points in the timeline of theonline course 104. The lecture 180 may define one or more user controlsthat allow the learner to control the lecture 180 and provide feedbackto the online education platform 102. The assessment 182 may include oneor more interactive questions to be answered by the learner via his/hercomputing device 174.

The education data 184 may include any type of visual information thatis presented to the learner as part of the online course 104. Forinstance, the education data 184 may include one or more images,captions to the lecture 180, graphs, text, audio, or any other type ofdata that is presented to the learners, as well as interactive controlsthat permits the learners to comment and provide feedback regarding theeducation content 136. The survey 188 may include one or more surveyquestions that elicit feedback about the online course 104 from thelearners. For example, the survey 188 may ask the learner to rate on ascale of 1 to 5 various topics relating to the online course 104. Thesurvey 188 may be presented towards the end of the course, or may surveythe learners at other parts of the online course 104 such as aftercompleting an assessment 182 or watching/listening to a lecture 180.

The online education platform 102 may partner with universities,schools, and/or organizations to provide the online courses 104. In someexamples, the online education platform 102 may provide hundreds orthousands of online courses 104 across many different types ofuniversities, schools, or organizations, and each online course 104 mayhave hundreds of learners (e.g., hundreds of computing devices 174connecting to a particular online course 104 via the online educationplatform 102). The online courses 104 may enable learners to watch shortlectures, take interactive quizzes and peer-graded assessments, andconnect with other learners and instructors. The online courses 104 mayinclude session-based online courses 106 and on-demand courses 108. Thesession-based online courses 106 may be associated with a courseschedule, and have specific start and end dates. Tests, if any, aretaken according to the course schedule. The on-demand courses 108 arecourses in which learners take on their own time, and guided byinstructors to meet individual needs.

The online education platform 102 allows many learners to take a singleonline course 104, and, as a result, provides a level of statisticaldata that was not possible with conventional courses or with onlineeducation platforms having a smaller capacity. For instance, in atypically class, the number of learners may be around 30. However, withrespect to a particular online course 104 provided by the onlineeducation platform 102, the number of learners may be over one hundredlearners. In other examples, the number of learners for a single onlinecourse 104 may be over 300. As such, the large number of learners for aparticular class permits the online education platform 102 to makecertain types of classifications and analysis that was not possible withconventional courses or smaller online platforms, as further explainedbelow.

The online education platform 102 may include an online course analyzer110 configured to provide, over the network, an instructor dashboard 154to be rendered by an instructor application 152 of a computing device150. The online course analyzer 110 may be configured to provide, overthe network, the instructor dashboard 154 that displays performance data112 regarding the learner's interaction and/or performance with theeducation content 136, as well as any survey results 114. For instance,the instructor dashboard 154 may provide the instructor with the mostrelevant and interesting data regarding the online class's performanceso that the instructor can make determinations on how well the learnersare understanding the education content 136, and determine whetherhis/her online course 104 could benefit from any adjustments.

Also, the instructor dashboard 154 may display online class information166 that provides background information about the leaners of the onlinecourse 104 such as the number of learners enrolled in the online course104, and information about each of the learners (e.g., name, school,etc.). Referring to FIG. 1, the computing device 150 refers to a deviceused by an instructor of an online course 104, and the instructor useshis/her computing device 150 to connect to the online education platform102 to view the learners' performance and engagement via the instructordashboard 154 and can make adjustments to the education content 136 viaan authoring tool 170 that interacts with a content editor 134 whichmakes any instructor edits compatible with a format of the onlineeducation platform 102 such that the re-published education content 136(reflecting the changed material) can be rendered across anyimplementation of the learner application 176 (e.g., native mobile, web,mobile web).

Generally, the online course analyzer 110 may be configured to analyzethe learners' performance and feedback with respect to the educationcontent 136, and provide statistical analysis on multiple differentlevels such as analyzing the quality of an assessment 182, comparingdifferent versions of assessments 182, evaluating parts of the onlinecourse 104 having low/high engagements, analyzing overall performance ofthe learners, and/or marking characterizations about different groups ofpeople, etc. In some examples, the instructor dashboard 154 may be auser interface (or series of user interfaces) that render theperformance data 112, the online class information 166, and the surveyresults 114.

Generally, the performance data 112 may provide information about thelearner's engagement and performance with the education content 136. Theperformance data 112 may indicate a level of learner engagement withvarious parts of the education content 136 of the online course 104(e.g., number or percentage of students dropping off), and the grades(or scores) on the assessments 182. Furthermore, the performance data112 may include analytic results 164 such as the number of students whocompleted the online course 104, the number of students who took anassessment 182, and the scores of the assessment(s) 182 by theindividual learners, the online course 104 as a whole, or acrossmultiple online courses 104. Then, based on this information, theinstructor may use the authoring tool 170 to adjust the educationcontent 136. For example, the instructor may see that a low percentageof learners correctly answer a question from the assessment 182. Then,while viewing this performance data 112, the instructor may start aprocess of altering the education content 136 (e.g., rewording aquestion from the assessment 182). In some examples, the authoring tool170 may be integrated into the instructor dashboard 154 in a manner thatallows the instructor to start an edit of an assessment 182 or changeother parts of the education content 136 while viewing the performancedata 112 (or other types of feedback) provided via the instructordashboard 154, as further explained below.

In further detail, the online course analyzer 110 may include a learnertracking unit 118 configured to track the learners' engagements with theeducation content 136. In some examples, the learner tracking unit 118may be configured to track each learner's clicks (or gestures) using thelearner application 176. In some examples, the learner tracking unit 118may be able to determine which learners are viewing and/or engaging withthe education content 136 and which learners are not viewing and/orengaging with the education content 136. In some examples, the learnermay be required to perform a certain action (e.g., selecting a control)while viewing the lecture 180 or interact with the education content 136in a certain way. For instance, if the learner fails to perform one ormore actions, the learner may be considered as not paying attention ordropped from the session or module of the online course 104.

The online course analyzer 110 may be configured to determine theperformance data 112 associated with the learners' engagement with theeducation content 136 including one or more engagement metrics 158indicating a level of engagement of the learners with the educationcontent 178, over time, during a session of the online course 104. Theone or more engagement metrics 158 may indicate a level of learnerengagement over the course of the online course 104. In some examples,the engagement metrics 158 may indicate a percentage of the learners whoviewed a particular lecture 180 (from the beginning to the end). In someexamples, the online course analyzer 110 may be configured to determinethe engagement metric(s) 158 based on the learners' tracked interactionsor engagements as collected by the learner tracking unit 118.

Also, in some examples, the performance data may include one or morevisualizations 168. For example, the engagement metrics 158 may berepresented by one or more visualizations 168. The visualization(a) 168may be a wave, chart, histogram, or any type of visual indicatorindicating a level of learner engagement with the education content 136.For example, the visual indicator may change based on the level oflearner engagement to reflect the level of attention/engagement with theonline course 104. In one example, the wave (or histogram) may be largerfor parts of the online course 104 having an increased rate of leanerengagement (increased engagement metrics 158). In some examples, if theengagement metrics 158 are below (or above) a threshold value, thecorresponding visualization 168 may be changed (e.g., displayed in red,bold, etc.). In some examples, the online course analyzer 110 isconfigured to continuously receive the relevant engagement metrics 158,and then populate the visualization 168 (and/or show the actual metrics)at intervals such as every 10 seconds, for example.

The online course analyzer 110 may include a grading unit 116 configuredto automatically grade the assessment 182 taken by the learners. Then,the online course analyzer 110 may use the grading results to determineone or more grading metrics 160 associated with the assessment 182(e.g., how many learners got question three right or wrong, etc.). Thegrading metrics 160 may be one or more values that represent theperformance of the leaners on one assessment 182 (or multipleassessments 182) across all the learners of the online course 104,certain subsets of learners, or individual learners. For example, thegrading unit 116 may be configured to automatically grade theassessments 182 taken by the learners, and provide one or more gradingmetrics 160 via the instructor dashboard 154 based on the gradedassessments 182. Also, the grading metrics 160 may be represented by oneor more visualizations 168. For example, with respect to a particularassessment 182, the grading metrics 160 may specify the percentage oflearners correctly answering each question.

The online education platform 102 may provide a first version of theassessment 182. Then, based on the performance data 112 (and potentiallythe survey results 114) provided via the instructor dashboard 154, theinstructor may determine that a particular part of the online course 104be changed. For instance, via the instructor dashboard 154, theinstructor may see that the grading metrics 160 associated with aparticular question on the assessment 182 is relatively low. Also, viathe instructor dashboard 154, the instructor may see that the engagementmetrics 158 for the lecture 180 and/or the education data 184 thatrelates to the subject matter of the low performing question arerelatively low (e.g., a certain percentage of learners dropping off).Then, while viewing the engagement metrics 158 and/or the gradingmetrics 160, the instructor may institute a change to the educationcontent 136, and the change may be carried out by the content editor 134which converts the education content 136 having a first format (e.g., atextual or HTML format entered by the instructor on the user interface)to a second format 142 (e.g., education markup language (EML) format)that is compatible with the online education platform 102 such that theonline education platform 102 can render the education content 136 withthe second format 142 across any implementation of the learnerapplication 176 (e.g., native mobile, web, mobile web). In someexamples, the change is a modification to one of the questions, therebycreating a second version of the assessment 182. In other examples, thechange is a modification to the lecture 180, or the education data 184(e.g., the reading material or the practice questions).

The online course analyzer 110 may include an assessment comparator 122configured to compare the first version of the assessment 182 with thesecond version of the assessment 182. The online course analyzer 110 maybe configured to provide results of the comparison as analytic results164 via the instructor dashboard 154. Also, it is noted that theanalytic results 164 may also include any other types of analysisperformed by the online course analyzer 110. In some examples, theassessment comparator 122 may be configured to compare the gradingmetrics 160 of the first version of the assessment 182 with the gradingmetrics 160 of the second version of the assessment 182, and determinethe difference in the performance data 112 between the two differentversion, e.g., indicating whether there was an improvement in the scoresrelating to the previous low scoring question. As a result, theinstructor can determine whether the changes to the assessment 182created a positive change.

The online course analyzer 110 may include a survey unit 120 configuredto provide the survey 188 to the learners of the online course 104. Thesurvey 188 may include one or more survey questions that elicit feedbackabout the online course 104 from the learners. For example, the survey188 may ask the learner to rate on a scale of 1 to 5 various topicsrelating to the online course 104. The survey 188 may be presentedtowards the end of the course, or may survey the learners at other partsof the online course 104 such as after completing an assessment 182 orwatching a lecture 180. The survey unit 120 may be configured to collectthe answers to the survey 188 and determine the survey results 114 to beprovided to the instructor via the instructor dashboard 154.

In some examples, the survey unit 120 may provide a first survey tolearners of an online course 104 associated with a first school, andprovide a second survey to learners of the online course 104 associatedwith a second school, where the first survey is equivalent to the secondsurvey. For example, the online education platform 102 may provide thesame online course 104 to students of multiple schools. The survey unit120 may provide the same survey 188 (e.g., a survey identifying the samequestions) across the different schools, and then compare the results ofthe first survey to results of the second survey.

The online education platform 102 may include a content evaluator 124configured to evaluate a quality of the education content 136 based onthe performance data 112 including the engagement metric(s) 158, theanalytic results 164, the grading metric(s) 160, and survey results 114.For example, the content evaluator 124 may evaluate various parts of theeducation content 136 based on the engagements metrics 158, the gradingmetrics 160, and the survey results 114. For example, the contentevaluator 124 may determine that a grading metric(s) 160 for aparticular assessment 182 (or portion of the assessment 182) is equal toor below a threshold value, an engagement metric 158(s) for a particularpart of the lecture and/or the education data 184 that corresponds tothe subject matter for the assessment 182 (or portion thereof) is belowor equal to a threshold value, and/or the survey results 114 about theonline course 104 (or portion thereof) indicates a relatively low score.Then, the content evaluator 124 may identify a portion of the onlinecourse 104 as potentially being low quality or a portion thatpotentially needs further improvement. In some examples, the contentevaluator 124 may use a weighted scoring algorithm that assigns weightsto various pieces of the performance data 112 and/or the survey results114, and computes a score for different parts or segments of theeducation content 136. If the score is above (or above) a certain value,the content evaluator 124 may identify that part or segment of theeducation content 136 as low quality (or high quality).

The online education platform 102 may include an alerting unit 130configured to generate an alert based on the quality of at least aportion of the educational content 136 being equal to or below athreshold value. For example, if the content evaluator 124 determinesthat a particular question of the assessment 182 is lower quality, thealerting unit 130 may be configured to generate an alert to theinstructor. In some examples, the alerting unit 130 may be configured toprovide the alert on an area of the instructor dashboard 154. In otherexamples, the alerting unit 130 may be configured to send an email ortext to the instructor.

In some examples, the online education platform 102 may include afeature comparator 126 configured to compare two or more features inorder to determine which feature is better than the others in terms ofthe performance data 112 and the survey results 114. In some examples,the feature comparator 126 is configured to perform A/B testing in viewof the performance data 112 to determine which of the features (e.g.,feature A or feature B) is better than the other. For example, thefeature comparator 126 may be configured to compare two differentversions or features of a particular aspect of the online course 104.

In further detail, the online education platform 102 may be configuredto provide the education content 136 with a first feature for an onlinecourse 104, and the online education platform 102 is configured toprovide the education content 136 with a second feature for an onlinecourse 104. The first feature may be different than the second feature.In some examples, the second feature is the opposite of the firstfeature. In one example, the first feature relates to providing a videoof the instructor in relation to the lecture 180, and the second featuredoes not provide a video of the instructor (just the audio). In someexamples, the online education platform 102 may provide the educationcontent 136 having the first feature to a first group within the onlinecourse 104, and provide the education content 136 having the secondfeature to a second group within the online course 104 (e.g., the secondgroup relates to a different set of learners than the first group). Inother examples, the education content 136 having the first feature maybe presented to a different session of the online course (e.g., samesubject matter but different group of learners) than the educationcontent 136 having the second feature. The feature comparator 126 maycompare the performance data 112 and the survey results 114 of theeducation content 136 having the first features with the performancedata 112 and the survey results 114 of the education content 136 havingthe second feature in order to determine which of the first feature orthe second feature is better than the other.

The online course analyzer 110 may include a learning management system(LMS) interface unit 132 configured to interface, over the network, withan LMS 172 associated with an organization. For example, the LMS 172 maybe associated with a particular school or university, and the LMS 172provides the administration, documentation, tracking, reporting, anddelivery of electronic education technology education courses ortraining programs associated with that school or university. An LMS 172may include systems for managing training and education records andsystems for distributing online or blended/hybrid courses over thenetwork with features for online collaboration. The LMS interface unit132 may be configured to communicate, over the network, with anorganization's LMS 172 in order to transmit and receive informationregarding learners who are part of the LMS's school as well as theonline education platform 102.

For example, there may be a group of students at school A (school Ahaving the LMS 172) who take an online course 104 provided by the onlineeducation platform 102. These students of school A take the onlinecourse 104 along with other learners (e.g., not part of school A). Theonline course analyzer 110 may determine the performance data 112 andthe survey results 114 for all the learners of the online course 104 inthe same manner described below. In some examples, the LMS interfaceunit 132 may be able to collect the performance data 112 and the surveyresults 114 for the students of school A, and send this information,over the network, to school A's LMS 172. In addition, the LMS interfaceunit 132 may be able to send analytic results 164 indicating how thatgroup of students performed relative to other students of the onlinecourse 104 provided by the online education platform 102 or anothergroup of students associated with school B. Also, it is noted that theLMS interface unit 132 may be configured to interface with a number ofLMSs 172, where each LMS 172 relates to a different organization.

An instructor may develop or modify an online course 104 using theauthoring tool 170. In some examples, the instructor may develop ormodify the assessment 182 by adding, deleting, or changing the contentfor the questions and answers of the assessment 182 using the instructordashboard 154 and/or the authoring tool 170. While viewing theengagement metrics 158, the grading metrics 160, the survey results 114,and/or the analytic results 164, the instructor may institute a changeto the education content 136. For instance, the authoring tool 170 maybe integrated into the instructor dashboard 154 such that the instructorcan initiate an edit of the education content 136 while viewing theperformance data 112 and the survey results 114. In other words, theinstructor may not need to log into a separate system or navigate adifferent part of the online education platform 102. Rather, theinstructor may activate a link, tab, control, button, etc. on the sameuser interface that provides the performance data 112 and/or the surveyresults 114, and this activation causes the online education platform102 to provide a user interface (or series of user interfaces) that apart of the authoring tool 170, which allows the instructor to change(add, delete, or modify) various parts of the education content 136including any quiz material.

The content editor 134 may interface with the authoring tool 170 to editor develop the education content 136 based on the performance data 112(and potentially the survey results 114 including changing at least aportion of the education content 136 based on the performance data 112.In some examples, the change can be published before a completion of theonline course 104. The authoring tool 170 may define a user interface(or series of user interfaces) that allows the instructor to edit theeducation content 136. In some examples, the user interface of theauthoring tool 170 may identify one or more text boxes for describingthe question and one or more text boxes for providing possible answers(e.g., multiple choice questions). The instructor may create or edit aquestion by typing text with or without a limited set of stylizedfeatures (e.g., underlying, bolding, strike-through, etc.), andinserting and/or defining math expressions, headers, images, videos,audio files, tables, lists, hyperlinks, and/or code blocks. In someexamples, the text boxes of the user interface of the authorizing tool170 may provide a tool bar that lists a plurality of tools such asinserting tables, inserting math expressions, inserting a header,underline, strike-through, and/or bold, etc.

In some examples, the authoring tool 170 may function as a documenteditor that allows the instructor to create the education content 136for the assessment 182 as he/she wants the learners to view thematerial. In some examples, the authoring tool 170 may indicate only thetype of features permitted by the second format 142. As explained laterin the specification, the education content 136 is eventually convertedto the second format 142, which may be a restricted set of XML tags (orblocks having a limited set of attributes). As such, the authoring tool170 may specify the type of editing features that is consummate in scopewith the restricted scope of the second format 142. For example, theauthoring tool 170 may not permit the recitation of a hyperlink to anaudio file external to the online education platform 102 because thistype of feature is not supported by the second format 142.

The content editor 134 may receive a modification to the educationcontent 136 (e.g., adding, deleting, or changing the assessment 182) inthe first format 138. The first format 138 may be a textual formatspecifying text (letters, numbers, and/or symbols without or withinstylized features), math expressions, images, videos, audio files,tables, lists, hyperlinks, and/or code blocks or HTML. In some examples,the first format 138 is the HTML format.

The content editor 134 may include an education content converter 140configured to convert the education content 136 having the first format138 to education content 136 having the second format 142. In someexamples, the second format 142 is considered a special education markuplanguage that can operate with the end client to render educationcontent (especially quizzes) with relatively good quality. For instance,on some platforms (e.g., mobile web), standard HTML tags do not renderwell when rendering special types of data such as the assessments 162.However, the education content 136 with the second format 142 isrendered with good design quality and uniform look and feel regardlessof the type of end client or platform (e.g., across mobile web, nativemobile application, or standard HTML web). Because the content editor134 converts from the first format 138 to the second format 142, theinstructor is unburdened with having to know the layout (or presentationdetails) of a particular platform (rather the layout is handled by theend client), and, therefore, the instructor can focus on the meaning ofthe content. For instance, the instructor can create the content usingthe text editor without having to know the details of HTML or whethercertain data can cause security concerns. Also, the use of the secondformat 142 improves the functioning of the online education platform 102itself because it improves the functioning and/or speed of populatingchanges within the online education platform 102. Furthermore, itlessens the security concerns associated with having many instructorsinsert content into the online education platform 102 by restricting thetypes of content that can be manipulated by the instructors.

In some examples, the second format 142 is a restricted XML format. Forexample, the restricted XML format may define the types of contentpermitted on the online education platform 102. In some examples, therestricted XML format may define a number of content types less thanwhat is traditionally provided with XML or HTML. In other examples, thesecond format 142 is a restricted HTML format. In some examples, therestricted HTML format may define a number of HTML tags that are lessthan what is traditionally provided by HTML. In some examples, therestricted XML or HTML format is defined in terms of blocks, where eachblock relates to a different type of content (e.g., text block, tableblock, audio block, list block, etc.). Also, each block is associatedwith a limited set of attributes. Stated another way, the XML or HTMLtags are defined with a limited set of attributes. In one example, thetext block may specify text in terms of letters, numbers, and systems,and may include math expressions with a limited set of stylized featuressuch as underlined, strikethrough, bold, etc. However, with respect tothe text block, other features may be excluded such as doublestrikethrough.

The content editor 134 may include a validation unit 144 configured tovalidate that the education content 136 is suitable for conversion bythe education content converter 140. In some examples, the validationunit 144 may perform a formality check on the education content 136 suchthat the education content 136 has the appropriate language to beconverted. For instance, the authoring tool 170 may specify theinsertion of a math expression using certain attributes, and, if thewrong attributes are used, the validation unit 144 may notify theinstructor to use the correct the attributes. After the educationcontent 136 is validated and converted, the updated education content136 may be provided to the learner application 176 of the computingdevice 174.

The learner application 176 may be configured to communicate with theonline education platform 102 over the network, and render and interactwith the education content 136 provided by the online course 104. Thelearner application 176 may be a native application (including nativemobile) or a browser-based application (mobile browser, or non-mobilebrowser) executing on an operating system of the computing device 174.The browser-based application may be referred to as mobile web or web.The learner application 176 may provide the education content 136 via aninterface allows a learner to interact with the online educationplatform 102. The computing device 174 may be a mobile computing device(e.g., a smart phone, a PDA, a tablet, or a laptop computer) or anon-mobile computing device (e.g., a desktop computing device). Thecomputing device 174 also includes various network interface circuitry,such as for example, a mobile network interface through which thecomputing device 174 can communicate with a cellular network, a Wi-Finetwork interface with which the computing device 174 can communicatewith a Wi-Fi base station, a Bluetooth network interface with which thecomputing device 174 can communicate with other Bluetooth devices,and/or an Ethernet connection or other wired connection that enables thecomputing device 174 to access the network.

In some examples, the learner application 176 also defines an authoringtool 190 that permits a learner to add material to the education content136. In some examples, the authoring tool 190 operates in the samemanner as the authoring tool 190. However, instead of editing quizzesand viewing performance information (which are actions typicallyperformed by instructors), the learners may add content such as projectmaterial, reading material, and/or other types of data. The contenteditor 134 may receive the learner's content in the first format 138,and the education content converter 140 may convert the content to thesecond format 142 in the same manner described above.

The instructor application 152 may be configured to communicate with theonline education platform 102 over the network. In some examples, theinstructor application 152 is different than the learner application176. In other examples, the instructor application 152 is the same orsubstantially the same as the learner application 176 except that theinstructor application 152 includes additional functionality associatedwith instructors (e.g., providing an instructor dashboard 154 integratedwith the authoring tool 170). For instance, a user may log into theonline education platform 102, and if the user has been identified as aninstructor, the online education platform 102 may provide thefunctionalities described with respect to the computing device 150. Onthe other hand, if the user has been identified as a learner, the onlineeducation platform 102 may provide the functionalities described withrespect to the computing device 174. The instructor application 152 mayrender the instructor dashboard 154 and the integrated authoring tool170. The instructor application 152 may be a native application or abrowser-based application executing on an operating system of thecomputing device 150.

The computing device 150 may be a mobile computing device (e.g., a smartphone, a PDA, a tablet, or a laptop computer) or a non-mobile computingdevice (e.g., a desktop computing device). The computing device 150 alsoincludes various network interface circuitry, such as for example, amobile network interface through which the computing device 150 cancommunicate with a cellular network, a Wi-Fi network interface withwhich the computing device 150 can communicate with a Wi-Fi basestation, a Bluetooth network interface with which the computing device150 can communicate with other Bluetooth devices, and/or an Ethernetconnection or other wired connection that enables the computing device150 to access the network.

In some examples, the online education platform 102 may be considered acloud-based online education service such that all or most of its mainfunctionalities are executed on the computing device 101. For instance,the computing device 174 or the computing device 150 may access theonline education platform 102 via the network through the use of anytype of network connections and/or application programming interfaces(APIs) in a manner that permits the online education platform 102, thelearner application 176, and the instructor application 152 tocommunicate with each other. In this regard, the term “cloud” or“cloud-aware” references the use of “cloud computing,” which, generallyspeaking, includes a style of computing in which computing resourcessuch as application programs and file storage are remotely provided overthe network such as the Internet, typically through a web browser. Forexample, many web browsers are capable of running applications (e.g.,Java applets), which can themselves be application programminginterfaces (“API's”) to more sophisticated applications running onremote servers. In the cloud computing paradigm, a web browserinterfaces with and controls an application program that is running on aremote server. Through the browser, the user can create, edit, save anddelete files on the remote server via the remote application program.Thus, it may be observed that the computing device 101 may alsorepresent an example of cloud computing. In other examples, a portion ofthe features of the online education platform 102 may be incorporatedinto the learner application 176 or the instructor application 152executing locally on the computing device 174 or the computing device150.

In some examples, the computing device 101 may include one or moreservers. In some examples, the computing device 101 may include one ormore processors (e.g., a processor coupled to a substrate), and anon-transitory computer-readable medium including executableinstructions that when executed by the one or more processors areconfigured to implement the functionalities of the online educationplatform 102.

FIG. 2 illustrates the education content 136 that is operable acrossmultiple platforms of the learner application 176 according to animplementation. In some examples, the second format 142 is an educationmarkup language (EML) format 242. The education content 136 having theEML format 242 is capable of being rendered across the learnerapplication 176 implemented as a mobile web 203, a web 205, or nativemobile 207. The mobile web 203 refers to access to the online educationplatform 102 through the use of a browser on a mobile phone (e.g.,mobile browser) that display the education content 136 as a webpage. Theweb 205 refers to access to the online education platform 102 throughthe use of a non-mobile browser that displays the education content 136as a webpage. The native mobile 207 may refer to a native applicationinstalled on a mobile. Typically, the education content 136 created bythe instructors is either plain text or HTML (e.g., the educationcontent 136 in the first format 138). However, the HTML tags for theassessments 182 do not render well (or properly) on the mobile web 203.For instance, with respect to certain types of data like the assessments182 and other types of education data 184, presentation quality may beless than optimal on certain types of clients (e.g., mobile web 203) ifthere were no such conversion to the EML format 242. Therefore,according to the embodiments, the education content converter 140converts the education content 136 having the first format 138 (e.g.,the HTML) to education content 136 having the EML format 242.

FIG. 3 illustrates a graphical representation of a perspective of theEML format 242 according to an implementation. The EML format 242 maydefine a plurality of blocks 241. The blocks 241 may be the internalrepresentation of the education content 136 that the instructorsgenerate for consumption. A block 241 may be a single unit ofinformation that can be rendered by any platform (e.g., the mobile web203, the web 205, or the native mobile 207) in a way that is best fittedfor that platform). In some examples, the blocks 241 may be considereduniversal to all three platforms in the sense that the language of EMLformat 242 does not require presentation information that is specific toa certain platform, but rather the EML format 242 is defined in a waythat wells the individual client to render the education content 136 inthe best manner. As such, the instructors may be able to focus on themeaning of their content.

In some examples, the EML format 242 is the language in which the blocks241 are written. In some examples, the EML format 242 is XML (orsubstantially XML). In some examples, the EML format 242 defines arestricted set of XML tags (e.g., with restricted attributes) and one ormore education-custom tags. For example, each block 241 corresponds to adifferent type of content and is restricted in the sense that certainfeatures are not allowed. As a result, native rendering on mobile andconsistent design across web and mobile platforms are enabled by usingthe EML-designed blocks 241.

In some examples, each block 241 is a section of content that can beinlined. Conversely, if a section of content that cannot be inlined,then it would not be suitable for inclusion within a block 241. Anycontent that introduces layout (e.g., an image) is separated into adifferent block 241 to allow clients to create an optimized layout(e.g., the web 205 may right-align an image, while the mobile web 205may center-align the same image). Any block 241 that has incompatiblerequirements with content that otherwise could have been inlined shouldbe separated out into a different block 241. For example, if links couldnot be surrounded by rich text, the links would have to be their ownblock 241, separate from the text block 241.

The plurality of blocks 241 include a text block 243, a heading block245, a list block 247, a table block 249, an image block 251, an audioblock 253, a code block 255, and an escape hatch block 257. In someexamples, the plurality of blocks 241 may include a video blockspecifying a video file. In some examples, the plurality of blocks 241may include other types of blocks.

The text block 243 may specify regular text with restricted formattingoptions such that one or more formatting options that normally would beavailable in HTML is not available in the EML format 242. In someexamples, the text block 243 includes text with a limited set of HTMLformatting tags. In some examples, the limited set of HTML formattingtags includes the following: strong (bold), emphasis <em> (italics),underline, strikethrough, a (text only), subscript, and superscript. Insome examples, the text block 243 includes math expressions. In someexamples, the text block 243 may include math expressions delimited byeither $$, \(\) (or inline equations) or \[\] (for block equations).Also, the text block 243 may specify one or more inline links which canbe used to link to an internal resource (e.g., internal to the onlineeducation platform 102) or an external page (e.g., external to theonline education platform 102). Also, with respect to the text, the textblock 243 may only allow a limited set of font color and sizes. Table 1below is an example of a text block 243 written in the EML format 242.

TABLE 1 (Text Block 243) EML Format 242 Rendered by Client <text> Thisis a bold example  <strong>bold</strong>example </text> <texthasMath=“true”> This is x²  This is $$x{circumflex over ( )}2$$ </text><text> This is a bold example from Coursera. <strong>bold</strong>example from <aHref=“http://www.coursera.org”>Coursera</a> </text>

The heading block 245 may specify a header. In some examples, theheading block 245 is similar to <h1>, <h2>, and <h3> HTML tags. Theheading block 245 may be capable of Rich text including mathexpressions. In some examples, the heading block 245 does not handlelinks. The heading blocks 245 may specify one of a plurality of levels(e.g., levels, 1, 2, or 3), and has an attribute that can specify math(e.g., has math=“true” or “false”). Table 2 is an example of a headingblock 245 written in the EML format 242.

TABLE 2 (Heading Block 245) EML Format 242 Rendered by Client <headinglevel=“1”> This is a heading example  This is a heading example <headinglevel=“1” hasMath=‘true”> Chapter 1:x²  Chapter 1: $$x{circumflex over( )}2$$ </heading>

The list block 247 is a block that is used to specify a list of blocks.In some examples, the list block 247 may identify only one block perlist item. In some examples, the list block 247 may have the followingattributes: bulletType: numbers (1 . . . 2), alphabets (a . . . b),bullets (*). Table 3 is an example of a List Block 247 written in theEML format 242.

TABLE 3 (List Block 247) EML Format 242 Rendered by Client <listbulletType=“numbers”> 1. Textblock1  <li> 2. Textblock2  <text>textblock1</text> 3. Textblock5  </li>  <li>  <text>textblock2</text>  </li>  <li>   <text>textblock5</text>  </li>

The table block 249 may be a block used to specify tables. In someexamples, the table block 249 may be filled out in row-wise order. Insome examples, the table block 249 may include the following attributes:rows (total number of rows in the table) and columns (column count ineach row in the table). Also, the table block 249 may specify table rows(<tr> </tr tags can be used to demarcate rows), table headers (<th></th> tags can be used to contain table header text, and these must bewithin a <tr> tag, and table headers can be defined with text blocks),and table data (<td> </td> are used to contain table data, and thesemust be within a <tr> tag, and the table data can be specified with textblocks). Table 4 is an example of a table block 249 written in the EMLformat 242.

TABLE 4 (TABLE Block 249) EML Format 242 Rendered by Client <tablerows=“3” columns =“2”> Textblock1 Textblock2  <tr> Mathtext1 Mathtext2  <th> Mathtext3 Mathtext4    <text>     textblock1    </text>   </th>   <th>    <text>     Textblock2    </text>   </th>   <tr>    <td>     <text hasMath=“true”>       Mathtext1      </text> ....

The image block 251 is a block used to specify an image. The image block251 may specify an image by reciting an internal URL. In some examples,the image block 251 may specify an image by only by reciting an internalURL. In some examples, if the specified image is scaled down on asmaller device, then clicking on it will open a bigger preview. In someexamples, the image block 251 may specify the URL (Src URL), alternativetext (in case the image fails to load), and a caption (optional). Table5 is an example of an image block 251 written in the EML format 242.

The audio block 253 may be a block used to identify audio data. In someexamples, the audio block 253 specifies an internally hosted audio file.In some examples, the audio block 253 only allows internally hostedaudio files. The audio block 253 may specify the audio URL, alternativetext (in case, the audio file does not load), and a caption (option).Table 6 below is an example of an audio block 253 defined with the EMLformat 242.

The code block 255 may be a differently styled block of text torepresent code (e.g., monospaced font). In some examples, the code block255 may include instructors that include literal newlines and tabs withno other styling (e.g., <strong>). Table 7 is an example of a code block255 defined with the EML format 242 and an example of a rendered codeblock 255 by the mobile web 203, the web 205, or the native mobile 207.

TABLE 7 (Code Block 255) EML Format 242 Rendered <code> If letunwrappedData = data? {  If let unwrappedData=data? {  Data.parse( );   Data.parse( );  }   } </code>

The escape hatch block 257 may be a block considered as a catch-allblock. In some examples, the escape hatch block 257 may be considered ananything-is-allowed HTML block that may be enabled for certaininstructors. For example, the escape hatch block 257 does not containthe type of restrictions placed on the other blocks, and, therefore,allows the instructors to be more creative in terms of designing theeducation content 136. In some examples, a warning may be provided tothe instructor that content created with this block may not be displayedon all platforms.

FIG. 4 illustrates a screenshot 400 of the authoring tool 170 of theinstructor application 152 that allows the instructor to edit theeducation content 136 according to an implementation. The authoring tool170 may define a text editor 423 that allows the instructor to edit theeducation content 136 by typing text with or without a limited set ofstylized features (e.g., underlying, bolding, strike-through, etc.), andinserting and/or defining math expressions, headers, images, videos,audio files, tables, lists, hyperlinks, and/or code blocks. After, theinstructor has edited the education content 136, the instructor canactivate a review and publish button 421 that proceeds to publish therevised content for the online course 104. For example, the contenteditor 134 receives the content entered via the text editor 423, and thevalidation unit 144 performs a formality check on the content enteredvia the text editor 423. If validated, the education content converter140 convers the content entered via the text editor 423 (which may be inHTML format) to the EML format 242. For example, the header text may beconverted into a heading block 245 (e.g., Table 2), the standard text(with or without math expressions) may be converted into a text block243 (e.g., Table 1), a table may be converted into a table block 249(e.g., Table 4), and an image may be converted into an image block(e.g., Table 5), and so forth. As a result, the content provided via thetext editor 423 may be provided to the end client or platform within theEML format 242, to be subsequently rendered on the learner's devices.

FIG. 5 illustrates a screenshot 500 of the authoring tool 170 of theinstructor application 152 that allows the instructor to edit theeducation content 136 according to an implementation. FIG. 5 is similarto FIG. 4 except that the authoring tool 170 of FIG. 5 depicts a toolbar 425 providing a plurality of tools to create the education content136. For example, H1, H2, and H3 provides different levels of headers(which are eventually converted to the heading block 245), as well asother tools (e.g., inserting tables, math expressions, etc.). Also, theauthoring tool 170 may specify the type of editing features within thetool bar 425 that is consummate in scope with the restricted scope ofthe EML format 242. For example, the authoring tool 170 may not permitthe recitation of a hyperlink to an audio file external to the onlineeducation platform 102 because this type of feature is not supported bythe EML format 242.

FIG. 6 illustrates an example of HTML as the first format 138 accordingto an implementation. For example, FIG. 6 illustrates the HTML versionof the education content 136 provided by the instructor in FIG. 4 beforethe education content 136 is converted into the EML format 242. FIG. 7illustrates the education content 136 provided by the instructor in FIG.4 which has been converted to the EML format 242 according to animplementation. FIG. 8 illustrates an example of a screenshot 800 of theeducation content 136 rendered by the learner application 176implemented as the native mobile 207 of the computing device 174according to an implementation. For example, the learner application 176rendered the education content 136 having the EML format of FIG. 7. FIG.9 illustrates an example of a screenshot 900 of the education content136 rendered by the learner application 176 implemented as the web 205of the computing device 174 according to an implementation. For example,the learner application 176 rendered the education content 136 havingthe EML format 242 of FIG. 7.

FIG. 10 illustrates a screenshot 1000 of the authoring tool 170 thatallows the instructor to change the assessment 182 of the educationcontent 136 in response to feedback according to an implementation. FIG.11 illustrates a screenshot 1100 of the authoring tool 170 that allowsthe instructor to change the assessment 182 of the education content 136in response to feedback according to an implementation. FIG. 12illustrates a screenshot 1200 of the authoring tool 170 that allows theinstructor to change the assessment 182 of the education content 136 inresponse to feedback according to an implementation. Referring to FIGS.10-12, using the tool bar 425, the authoring tool 170 permits theinstructor to edit the assessment 182. Also, as shown in FIGS. 10 and12, the authoring tool 170 is integrated with the instructor dashboard154 in the sense that the instructor can toggle between the authoringtool 170 and the instructor dashboard 154 by selecting an edit quizbutton 453 or a statistics button 451 associated with the instructordashboard 154. Also, the interface of the authoring tool 170 provides agrading metric 160 that indicates the passing threshold for the onlinecourse 104. The instructor may obtain a perspective of how well thelearners are engaged and performing while viewing the instructordashboard 154 (e.g., activating the statistics button 451), and thenquickly initiate an edit of the assessment by activating the edit quizbutton 453.

FIG. 13 illustrates a screenshot 1300 of the instructor dashboard 154according to an implementation. As shown in FIG. 13, the instructordashboard 154 depicts a portion of the assessment 182, and providesgrading metrics 160 associated with a question of the assessment 182.The grading metrics 160 of FIG. 13 depict the percentage of learnersfirst attempting the question, and the percentage of learners lastattempting the question. Also, the authoring tool 170 is integratedwithin the instructor dashboard 154 in the sense that the instructor caninitiate an edit of the question of the assessment 182 by activating theedit question button 455 on the instructor dashboard 154.

FIG. 14 illustrates a screenshot 1400 of the instructor dashboard 154depicting the continuation rate and first attempt average score for aportion of the online course 104 according to an implementation. FIG. 15illustrates a screenshot 1500 of the instructor dashboard 154 depictingthe continuation rate and first attempt average score for a portion ofthe online course 104 according to an implementation. Referring to FIGS.14-15, the instructor dashboard 154 provides engagement metrics 158 inthe form of a continuation rate, and grading metrics 160 in the form ofthe first attempt average score for a particular part of the onlinecourse 104. The continuation rate may indicate the percentage oflearners that have completed a particular segment or module of theonline course 104.

FIG. 16 illustrates a screenshot 1600 of the instructor dashboard 154depicting analytic results 164 according to an implementation. FIG. 17illustrates a screenshot 1700 of the instructor dashboard 154 depictinganalytic results 164 according to another implementation. Referring toFIGS. 16-17, the analytic results 164 may include the percentage oflearners having completed the lecture 180, and, of these, the percentageof learners having completed an assessment 182, and the percentage oflearners have completed a module, and the percentage of learners havingcompleted the online course 104.

FIG. 18 illustrates a screenshot 1800 of the instructor dashboard 154depicting grading metrics 160 by questions for an assessment 182according to an implementation. The grading metrics 160 of FIG. 18depict the first attempt average score and the last attempt averagescore for each question in the assessment 182.

FIG. 19 illustrates a screenshot 1900 of the instructor dashboard 154depicting various pieces of performance data 112 for an assessment 182of an online course 104 according to an implementation. Also, theauthoring tool 170 is integrated within the instructor dashboard 154 inthe sense that the instructor can initiate an edit of the assessment 182by activating the edit quiz button 453 on the instructor dashboard 154.Also, the instructor can toggle between the authoring tool 170 and theinstructor dashboard 154 by selecting the statistics button 451 or theedit quiz button 453. The performance data 112 of FIG. 19 depicts thecontinuation rate, the amount of learners who took the assessment 182,the average attempts per learner, the first attempt average score, thelast attempt average score, and one or more visualizations thatrepresent the grading of the assessment 182.

FIG. 20 illustrates a screenshot 2000 of the instructor dashboard 154depicting various pieces of performance data 112 for a first versionassessment 182 of an online course 104. FIG. 21 illustrates a screenshot2100 of the instructor dashboard 154 depicting various pieces ofperformance data 112 for a second version assessment 182 of the onlinecourse 104. Referring to FIGS. 20-21, the authoring tool 170 isintegrated within the instructor dashboard 154 in the sense that theinstructor can initiate an edit of the first version assessment 182-1(as well as the second version assessment 182-2) by activating the editquiz button 453 on the instructor dashboard 154. Also, the instructorcan toggle between the authoring tool 170 and the instructor dashboard154 by selecting the statistics button 451 or the edit quiz button 453.When the statistics button 451 is activated, the instructor dashboard154 can depict the performance data 112 as including the continuationrate, the amount of learners who took the assessment 182, the averageattempts per learner, the first attempt average score, the last attemptaverage score, and one or more visualizations that represent the gradingof the assessment 182 (the first version assessment 182-1 or the secondversion assessment 182-2).

In one example, the online education platform 102 may provide the firstversion assessment 182. Then, based on the performance data 112 (andpotentially the survey results 114) provided via the instructordashboard 154 (when the statistics button 451 is activated), theinstructor may determine that a particular part of the assessment 182should be changed. For instance, via the instructor dashboard 154, theinstructor may see that the grade distribution is relatively low. Also,via the instructor dashboard 154, the instructor may see that thecontinuation rate is relatively low. Then, the instructor may institutea change to the assessment 182 to create the second version assessment182-2, and the change may be carried out by the content editor 134 whichconverts the education content 136 having the HTML or text format to theEML format 242 that is compatible with the online education platform 102such that the online education platform 102 can render the secondversion assessment 182-2 with the EML format 242 across any platform ofthe learner's computing device (e.g., native mobile, web, mobile web).Then, the instructor can view the performance data 112 associated withthe second version assessment 182-2 (e.g., FIG. 21) and determinewhether there was an improvement in the performance data 112.

FIG. 22 illustrates a screenshot 2200 of the instructor dashboard 154depicting the survey results 114 according to an implementation. Thesurvey results 114 of FIG. 22 depict the percentage of students choosingone of the survey answers for a series of topics.

FIG. 23 illustrates a flowchart 2300 depicting example operations of thesystem 100 of FIG. 1 according to an implementation. Although FIG. 23 isillustrated as a sequential, ordered listing of operations, it will beappreciated that some or all of the operations may occur in a differentorder, or in parallel, or iteratively, or may overlap in time.

An online course may be provided over a network to a plurality ofcomputing devices, where the online course provides education content inwhich learners view and interface with the education content (2302). Forexample, the online education platform 102 may be configured to providethe online course 104 over a network to the plurality of computingdevices 150, where the online course 104 provides education content 136in which learners view and interact with the education content 136.

Performance data associated with learners' engagement with the educationcontent may be determined including an engagement metric indicating alevel of engagement of the learners with the education content during asession of the online course (2304). For example, the online educationplatform 102 may include an online course analyzer 110 configured todetermine performance data 112 associated with learners' engagement withthe education content 136 including an engagement metric 158 indicatinga level of engagement of the learners with the education content 136during a session of the online course 104. In some examples, the onlinecourse analyzer 110 includes a learner tracking unit 118 configured totrack learners' interactions with the education content 136 during thesession of the online course 104, and the online course analyzer 110 isconfigured to determine the engagement metric 158 based on the learners'interactions.

An instructor dashboard may be provided on a computing device associatedwith an instructor of the online course, where the instructor dashboardprovides the performance data (2306). For example, the online courseanalyzer 110 may be configured to provide an instructor dashboard 154 ona computing device 150 associated with an instructor of the onlinecourse 104.

The education content may be edited based on the performance dataincluding changing at least a portion of the education content based onthe performance data before a completion of the online course (2308).For example, the content editor 134 may be configured to edit theeducation content 136 based on the performance data 112 includingchanging at least a portion of the education content 136 based on theperformance data 112 before a completion of the online course 104. Insome examples, the content editor 134 is configured to interface with anauthoring tool 170 executing on the computing device 150 associated withthe instructor, where the authoring tool 170 is integrated within theinstructor dashboard 154 such that the instructor can initiate an editof the education content 136 while viewing the performance data 112.

In some examples, the online course analyzer 110 includes a grading unit116 configured to automatically grade assessments 182 taken by thelearners, and provide one or more grading metrics 160 via the instructordashboard 154 based on the graded assessments 182. In some examples, theonline education platform 102 is configured to provide a first versionof an assessment 182 of the online course 104, and the content editor134 is configured to change at least a portion of the first version ofthe assessment 182 to create a second version of the assessment 182. Insome examples, the online course analyzer 110 includes an assessmentcomparator 122 configured to compare the first version of the assessment182 with the second version of the assessment 182, where the onlinecourse analyzer 110 is configured to provide results of the comparisonvia the instructor dashboard 154.

In some examples, the online course analyzer 110 includes a contentevaluator 124 configured to evaluate a quality of the education content136 based on the performance data 112, and the online course analyzer110 may include an alerting unit 130 configured to generate an alertbased on a quality of at least a portion of the educational content 136being equal to or below a threshold value.

In some examples, the online education platform 102 is configured toprovide the education content 136 with a first feature, and the onlineeducation platform 102 is configured to provide the education content136 with a second feature, where the online course analyzer 110 includesa feature comparator 126 configured to compare performance data 112having the first feature with performance data 112 having the secondfeature determine which of the first feature or the second feature isbetter than the other. In some examples, the online course analyzer 110is configured to provide a histogram reflecting a grade distribution ofan assessment 182 of the online course 104. In some examples, the onlinecourse analyzer 110 includes a survey unit 120 configured to provide afirst survey to learners of an online class associated with a firstschool, and provide a second survey to learners of the online classassociated with a second school, where the first survey being equivalentto the second survey, and the survey unit 120 may be configured tocompare results of the first survey to results of the second survey.

FIG. 24 illustrates a flowchart 2400 depicting example operations of thesystem 100 of FIG. 1 according to an implementation. Although FIG. 24 isillustrated as a sequential, ordered listing of operations, it will beappreciated that some or all of the operations may occur in a differentorder, or in parallel, or iteratively, or may overlap in time.

An online course may be provided over a network to a plurality ofcomputing devices, where the online course provides education content inwhich learners view and interact with the education content (2402). Forexample, the online education platform 102 may be configured to providethe online course 104 over a network to a plurality of computing devices174, where the online course 104 provides education content 136 in whichlearners view and interact with the education content 136.

An authoring tool may be provided on a computing device associated withan instructor of the online course, where the authoring tool configuredto develop or change an assessment of the education content associatedwith the online course (2404). For example, the content editor 134 maybe configured to provide the authoring tool 170 on the computing device150 associated with an instructor of the online course 104, where theauthoring tool 170 may be configured to develop or change the assessment182 of the education content 136 associated with the online course 104.In some examples, the instructor can change other portions of theeducation content 136 such as the lecture 180, and the education data184. Also, the content editor 134 may provide the authoring tool 190 onthe computing devices 174 associated with the learners such that thelearners can publish material to the online course 104. In someexamples, the authoring tool 170 defines a tool bar 425 identifying aplurality of tools used to edit the education content 136, where theplurality of tools are a restricted set of tools that is consummate inscope with the second format 142 (e.g., the EML format 242).

Education content that defines the assessment may be received via theauthoring tool in a first format (2406). For example, the content editor134 may receive the education content that defines the assessment 182via the authoring tool 170 in the first format. In some examples, thefirst format is an HTML format. In some examples, the first format is atext format. In some examples, the first format is a combination of anHTML format and text format.

The first format may be converted to a second format (2408). The contenteditor 134 may include an education content converter 140 configured toconvert the first format 138 to a second format 142. In some examples,the second format 142 is the EML format 242. In some examples, the EMLformat 242 defines a plurality of blocks 241 using XML, and each of theplurality of blocks 241 correspond to a different type of data content.In some examples, the XML format defines each block of the plurality ofblocks 241 with restricted attributes that limits a block 241 to aparticular type of data content. In some examples, the education contentconverter 140 is configured to convert the first format 138 to thesecond format 142 by converting a hypertext markup language (HTML)format to the EML format 242, where the EML format 242 defines theplurality of blocks 241 with restricted attributes that limit each block241 to a different type of data content. In some examples, the pluralityof blocks 241 include one or more (or any combination of) a text block243, a heading block 245, list block 247, a table block 249, an imageblock 251, code block 255, and an audio block 253. In some examples, theplurality of blocks 241 further includes an escape hatch block 257.

The education content that defines the assessment having the secondformat may be provided to the plurality of computing devices associatedwith the learners (2410). For example, the content editor 134 may beconfigured to provide the education content that defines the assessment182 over the network to the plurality of computing devices 174associated with the learners.

In the above description, numerous details are set forth. It will beapparent, however, to one of ordinary skill in the art having thebenefit of this disclosure, that implementations of the disclosure maybe practiced without these specific details. In some instances,well-known structures and devices are shown in block diagram form,rather than in detail, in order to avoid obscuring the description.

Some portions of the detailed description are presented in terms ofalgorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared and otherwise manipulated. It has provenconvenient at times, principally for reasons of common usage, to referto these signals as bits, values, elements, symbols, characters, terms,numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the above discussion, itis appreciated that throughout the description, discussions utilizingterms such as “identifying,” “determining,” “calculating,” “updating,”“transmitting,” “receiving,” “generating,” “changing,” or the like,refer to the actions and processes of a computer system, or similarelectronic computing device, that manipulates and transforms datarepresented as physical (e.g., electronic) quantities within thecomputer system's registers and memories into other data similarlyrepresented as physical quantities within the computer system memoriesor registers or other such information storage, transmission or displaydevices.

Implementations of the disclosure also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes, or it may comprise a generalpurpose computer selectively activated or reconfigured by a computerprogram stored in the computer. Such a computer program may be stored ina non-transitory computer readable storage medium, such as, but notlimited to, any type of disk including floppy disks, optical disks,CD-ROMs and magnetic-optical disks, read-only memories (ROMs), randomaccess memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards,flash memory, or any type of media suitable for storing electronicinstructions.

The words “example” or “exemplary” are used herein to mean serving as anexample, instance, or illustration. Any aspect or design describedherein as “example’ or “exemplary” is not necessarily to be construed aspreferred or advantageous over other aspects or designs. Rather, use ofthe words “example” or “exemplary” is intended to present concepts in aconcrete fashion. As used in this application, the term “or” is intendedto mean an inclusive “or” rather than an exclusive “or”. That is, unlessspecified otherwise, or clear from context, “X includes A or B” isintended to mean any of the natural inclusive permutations. That is, ifX includes A; X includes B; or X includes both A and B, then “X includesA or B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Moreover, use of the term “an implementation” or “one embodiment”or “an implementation” or “one implementation” throughout is notintended to mean the same embodiment or implementation unless describedas such. Furthermore, the terms “first,” “second,” “third,” “fourth,”etc. as used herein are meant as labels to distinguish among differentelements and may not necessarily have an ordinal meaning according totheir numerical designation.

The algorithms and displays presented herein are not inherently relatedto any particular computer or other apparatus. Various general purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct a more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear from the description below.In addition, the present disclosure is not described with reference toany particular programming language. It will be appreciated that avariety of programming languages may be used to implement the teachingsof the disclosure as described herein.

The above description sets forth numerous specific details such asexamples of specific systems, components, methods and so forth, in orderto provide a good understanding of several implementations of thepresent disclosure. It will be apparent to one skilled in the art,however, that at least some implementations of the present disclosuremay be practiced without these specific details. In other instances,well-known components or methods are not described in detail or arepresented in simple block diagram format in order to avoid unnecessarilyobscuring the present disclosure. Thus, the specific details set forthabove are merely examples. Particular implementations may vary fromthese example details and still be contemplated to be within the scopeof the present disclosure.

It is to be understood that the above description is intended to beillustrative and not restrictive. Many other implementations will beapparent to those of skill in the art upon reading and understanding theabove description. The scope of the disclosure should, therefore, bedetermined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A system comprising: at least one processor; anon-transitory computer-readable medium configured to store executableinstructions that when executed by the at least one processor areconfigured to implement an online education platform configured toprovide an online course over a network to a plurality of computingdevices, the online course providing education content in which learnersview and interact with the education content, the online educationplatform including: an online course analyzer configured to provide aninstructor dashboard on a computing device associated with an instructorof the online course, the online course analyzer configured to determineperformance data associated with learners' engagement with the educationcontent including an engagement metric indicating a level of engagementof the learners with the education content during a session of theonline course; and a content editor configured to edit the educationcontent based on the performance data including changing at least aportion of the education content based on the performance data before acompletion of the online course.
 2. The system of claim 1, wherein thecontent editor is configured to interface with an authoring toolexecuting on the computing device associated with the instructor, theauthoring tool being integrated within the instructor dashboard suchthat the instructor can initiate an edit of the education content whileviewing the performance data.
 3. The system of claim 1, wherein theonline course analyzer includes a learner tracking unit configured totrack learners' interactions with the education content during thesession of the online course, and the online course analyzer isconfigured to determine the engagement metric based on the learners'interactions.
 4. The system of claim 1, wherein the online courseanalyzer includes a grading unit configured to automatically gradeassessments taken by the learners, and provide one or more gradingmetrics via the instructor dashboard based on the graded assessments. 5.The system of claim 1, wherein the online education platform isconfigured to provide a first version of an assessment of the onlinecourse, and the content editor is configured to change at least aportion of the first version of the assessment to create a secondversion of the assessment, the online course analyzer including: anassessment comparator configured to compare the first version of theassessment with the second version of the assessment, wherein the onlinecourse analyzer is configured to provide results of the comparison viathe instructor dashboard.
 6. The system of claim 1, wherein the onlinecourse analyzer includes a content evaluator configured to evaluate aquality of the education content based on the performance data, theonline course analyzer including an alerting unit configured to generatean alert based on a quality of at least a portion of the educationalcontent being equal to or below a threshold value.
 7. The system ofclaim 1, wherein the online education platform is configured to providethe education content with a first feature, and the online educationplatform is configured to provide the education content with a secondfeature, wherein the online course analyzer includes a featurecomparator configured to compare performance data having the firstfeature with performance data having the second feature determine whichof the first feature or the second feature is better than the other. 8.The system of claim 1, wherein the online course analyzer is configuredto provide a histogram reflecting a grade distribution of an assessmentof the online course.
 9. The system of claim 1, wherein the onlinecourse analyzer includes a survey unit configured to provide a firstsurvey to learners of an online class associated with a first school,and provide a second survey to learners of the online class associatedwith a second school, the first survey being equivalent to the secondsurvey, the survey unit configured to compare results of the firstsurvey to results of the second survey.
 10. A non-transitorycomputer-readable medium storing executable instructions that whenexecuted by at least one processor are configured to implement an onlineeducation platform, the online education platform configured to providean online course over a network to a plurality of computing devices, theonline course providing education content in which learners view andinteract with the education content, the online education platformconfigured to: determine performance data associated with learners'engagement with the education content including an engagement metricindicating a level of engagement of the learners with the educationcontent during a session of the online course, and a grading metricassociated with an assessment of the education content; provide aninstructor dashboard on a computing device associated with an instructorof the online course, the instructor dashboard providing the engagementmetric and the grading metric, the instructor dashboard providing a linkto initiate an edit of the assessment in relation to at least one of theengagement metric and the grading metric; and provide an authoring toolupon activation of the link, the authoring tool defining a text editorconfigured to receive a modification to education content that definesthe assessment.
 11. The non-transitory computer-readable medium of claim10, wherein the online education platform is configured to: tracklearners' interactions with the education content during the session ofthe online course and determine the engagement metric based on thelearners' interactions.
 12. The non-transitory computer-readable mediumof claim 10, wherein the online education platform is configured to:automatically grade the assessment taken by each of the learners whocompleted the assessment and provide the grading metric via theinstructor dashboard based on the graded assessment.
 13. Thenon-transitory computer-readable medium of claim 10, wherein the onlineeducation platform is configured to: provide a first version of theassessment; change at least a portion of the first version of theassessment to create a second version of the assessment; compare thefirst version of the assessment with the second version of theassessment; and provide results of the comparison via the instructordashboard.
 14. The non-transitory computer-readable medium of claim 10,wherein the online education platform is configured to: evaluate aquality of the education content based on the performance data; andgenerate an alert based on a quality of at least a portion of theeducational content being equal to or below a threshold value.
 15. Thenon-transitory computer-readable medium of claim 10, wherein the onlineeducation platform is configured to: provide the education content witha first feature; provide the education content with a second feature;and compare performance data having the first feature with performancedata having the second feature determine which of the first feature orthe second feature is better than the other.
 16. The non-transitorycomputer-readable medium of claim 10, wherein the online educationplatform is configured to provide a histogram reflecting a gradedistribution of the assessment.
 17. A method for implementing an onlineeducation platform that provides an online course over a network to aplurality of computing devices in which learners view and interact witheducation content of the online course, the method comprising:determining, by at least one processor, performance data associated withlearners' engagement with the education content including an engagementmetric indicating a level of engagement of the learners with theeducation content during a session of the online course and a gradingmetric associated with an assessment of the education content;providing, by the at least one processor, an instructor dashboard on acomputing device associated with an instructor of the online course, theinstructor dashboard providing the engagement metric and the gradingmetric, the instructor dashboard providing a link to initiate an edit ofthe assessment in relation to at least one of the engagement metric andthe grading metric; and providing, by the at least one processor, anauthoring tool upon activation of the link, the authoring tool defininga text editor configured to receive a modification to education contentthat defines the assessment.
 18. The method of claim 17, furthercomprising: tracking, by the at least one processor, learners'interactions with the education content during the session of the onlinecourse; and determining, by the at least one processor, the engagementmetric based on the learners' interactions.
 19. The method of claim 17,further comprising: automatically grading, by the at least oneprocessor, the assessment taken by each of the learners who completedthe assessment; and providing, by the at least one processor, thegrading metric via the instructor dashboard based on the gradedassessment.
 20. The method of claim 17, further comprising: providing,by the at least one processor, the education content with a firstfeature; providing, by the at least one processor, the education contentwith a second feature; and comparing, by the at least one processor,performance data having the first feature with performance data havingthe second feature determine which of the first feature or the secondfeature is better than the other.